Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 8 of 8 for “"Multimodal AI"”.
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Multimodal AI for Hospital Readmission Prediction Among Older Adults
This thesis develops a multimodal artificial intelligence (AI) model to predict 30-day hospital readmission risk among older adults, including those receiving home care. The aim is to create a robust predictive framework that leverages comprehensive patient data collected during hospitalisation to …
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Multimodal AI Tools for Predicting Neurological and Neurodevelopmental Trajectories
L'abstract è presente nell'allegato / the abstract is in the attachment
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A Study on Multimodal AI for Mild Cognitive Impairment Detection
<p>Mild Cognitive Impairment (MCI) is an early stage of memory loss or other cognitive ability loss in individuals who maintain the ability to independently perform most activities of daily living. It is considered a transitional stage between normal cognitive stage and more severe cognitive …
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Alive Scene: Participatory Multimodal AI Framework for Collective Narratives in Dynamic 3D Scene
… through the Contrastive Language-Image Pretraining (CLIP) model. These methods are currently among the most popular and efficient. The platform continually enriches its collection of users' views and interpretations through interactions with this semantic AI system, enabling the archiving of …
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Data-Driven General Purpose Foundation Models for Computational Pathology
… encoder models for pathology images: one using paired image-text data, and another leveraging self-supervised learning on large-scale unlabeled images. Additionally, I will examine downstream applications of these foundation models, including zero-shot transfer to gigapixel whole slide images and …
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Analyzing Multimodal Interactions through Improved Partial Information Decomposition Estimation
Multimodal AI aims to build comprehensive models by integrating information from diverse sensory inputs such as text, audio, and vision. However, significant challenges remain in understanding how these different modalities interact and contribute to downstream tasks. In particular, we seek to …
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Multimodal Machine Learning for mCRC: Designing a Radiopathomics Pipeline for Therapy Response Prediction
L'abstract è presente nell'allegato / the abstract is in the attachment
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Multimodal Foundation Models through the Lens of Security: Robust Deepfake Detection and Adversarial Resilience
Generative AI plays a crucial role in processing and interpreting information, making its reliability more important than ever. Multimodal Foundation Models (MFM), which drive the latest innovations in generative AI, have a significant impact on our daily lives. These models can process multiple …